import spaces import gradio as gr import subprocess from PIL import Image,ImageEnhance,ImageFilter import json import numpy as np from skimage.exposure import match_histograms import mp_box ''' Face landmark detection based Face Detection. https://ai.google.dev/edge/mediapipe/solutions/vision/face_landmarker from model card https://storage.googleapis.com/mediapipe-assets/MediaPipe%20BlazeFace%20Model%20Card%20(Short%20Range).pdf Licensed Apache License, Version 2.0 Train with google's dataset(more detail see model card) Not Face Detector based https://ai.google.dev/edge/mediapipe/solutions/vision/face_detector Bacause this is part of getting-landmark program and need control face edge. So I don't know which one is better.never compare these. ''' def color_match(base_image,cropped_image): reference = np.array(base_image) target =np.array(cropped_image) matched = match_histograms(target, reference,channel_axis=-1) return Image.fromarray(matched) def select_box(boxes,box_type): if box_type == "type-3": box = boxes[2] elif box_type =="type-2": box = boxes[1] elif box_type =="type-1": box = boxes[0] else:#never happen box=[0,0,image.size[0],image.size[1]] box_width = box[2] box_height = box[3] box = mp_box.xywh_to_xyxy(box) return box,box_width,box_height def resize_image_in_box(image,box_width,box_height,keep_aspect=True,resampling=None): aspect_ratio = image.width / image.height if box_width / box_height >= aspect_ratio: new_width = int(box_height * aspect_ratio) new_height = box_height else: new_width = box_width new_height = int(box_width / aspect_ratio) if resampling == None:#automatic image_area = image.width * image.height if box_width * box_height > image_area: resampling = Image.Resampling.BICUBIC else: resampling = Image.Resampling.LANCZOS resized = image.resize((new_width,new_height),resampling) offset_x = int((box_width -new_width)/2) offset_y = int((box_height -new_height)/2) return resized,offset_x,offset_y def process_images(image,replace_image=None,replace_image_need_crop=False,box_type="type-3",fill_color_mode=False,fill_color="black",custom_color="rgba(255,255,255,1)",image_size=1024,margin_percent=0,filter_value="None",match_color=True,progress=gr.Progress(track_tqdm=True)): if image == None: raise gr.Error("Need Image") # choose box image_width,image_height = image.size boxes,mp_image,face_landmarker_result = mp_box.mediapipe_to_box(image) box,box_width,box_height = select_box(boxes,box_type) # replace-mode if replace_image!=None: print("replace mode") if replace_image_need_crop: replace_boxes,mp_image,face_landmarker_result = mp_box.mediapipe_to_box(replace_image) replace_box,replace_box_width,replace_box_height = select_box(replace_boxes,box_type) keep_aspect = True # this is for fill_color_mode exported image if fill_color_mode: if replace_image_need_crop: cropped = replace_image.crop(replace_box) cropped,off_x,off_y = resize_image_in_box(cropped,box_width,box_height,keep_aspect) else: cropped = replace_image.crop(box) off_x = int((box_width -cropped.width)/2) off_y = int((box_height -cropped.height)/2) if match_color: cropped = color_match(image.crop(box),cropped) #just paste base-face area image.paste(cropped,[box[0]+off_x,box[1]+off_y]) return image else:#scale mode # box expand by margin if margin_percent>0: h_margin = int(box_width*margin_percent/100) v_margin = int(box_height*margin_percent/100) box[0] = max(0,box[0]-h_margin) box[1] = max(0,box[1]-v_margin) box[2] = min(image_width-1,box[2]+h_margin) box[3] = min(image_height-1,box[3]+v_margin) box_width = box[2]-box[0] box_height = box[3]-box[1] if replace_image_need_crop: replace_image = replace_image.crop(replace_box) replace_resized,off_x,off_y = resize_image_in_box(replace_image,box_width,box_height,keep_aspect) if match_color: replace_resized = color_match(image.crop(box),replace_resized) image.paste(replace_resized,[box[0]+off_x,box[1]+off_y]) return image # box expand by margin if margin_percent>0: h_margin = int(box_width*margin_percent/100) v_margin = int(box_height*margin_percent/100) box[0] = max(0,box[0]-h_margin) box[1] = max(0,box[1]-v_margin) box[2] = min(image_width-1,box[2]+h_margin) box[3] = min(image_height-1,box[3]+v_margin) # crop-mode if fill_color_mode: # choose color color_map={ "black":[0,0,0,1], "white":[255,255,255,1], "gray":[127,127,127,1], "red":[255,0,0,1], "brown":[92,33,31,1], "pink":[255,192,203,1], } if fill_color == "custom": color_value = custom_color.strip("rgba()").split(",") color_value[0] = int(float(color_value[0])) color_value[1] = int(float(color_value[1])) color_value[2] = int(float(color_value[2])) else: color_value = color_map[fill_color] cropped = image.crop(box) img = Image.new('RGBA', image.size, (color_value[0], color_value[1], color_value[2])) img.paste(cropped,[box[0],box[1]]) return img else: #scale up mode cropped = image.crop(box) resized = resize_image_by_max_dimension(cropped,image_size) filter_map={ "None":None, "Blur":ImageFilter.BLUR,"Smooth More":ImageFilter.SMOOTH_MORE,"Smooth":ImageFilter.SMOOTH,"Sharpen":ImageFilter.SHARPEN,"Edge Enhance":ImageFilter.EDGE_ENHANCE,"Edge Enhance More":ImageFilter.EDGE_ENHANCE_MORE } if filter_value not in filter_map: raise gr.Error(f"filter {filter_value} not found") if filter_value != "None": #resized = resized.filter(ImageFilter.SHARPEN) #Gimp's weak 0.1-0.2? enhancer = ImageEnhance.Sharpness(resized) resized = resized.filter(filter_map[filter_value]) #resized = enhancer.enhance(sharpen_value) return resized def resize_image_by_max_dimension(image, max_size, resampling=Image.Resampling.BICUBIC): image_width, image_height = image.size max_dimension = max(image_width, image_height) ratio = max_size / max_dimension new_width = int(image_width * ratio) new_height = int(image_height * ratio) return image.resize((new_width, new_height), resampling) def read_file(file_path: str) -> str: """read the text of target file """ with open(file_path, 'r', encoding='utf-8') as f: content = f.read() return content css=""" #col-left { margin: 0 auto; max-width: 640px; } #col-right { margin: 0 auto; max-width: 640px; } .grid-container { display: flex; align-items: center; justify-content: center; gap:10px } .image { width: 128px; height: 128px; object-fit: cover; } .text { font-size: 16px; } """ #css=css, def update_button_label(image): if image == None: print("none replace") return gr.Button(visible=True),gr.Button(visible=False),gr.Row(visible=True),gr.Row(visible=True) else: return gr.Button(visible=False),gr.Button(visible=True),gr.Row(visible=False),gr.Row(visible=False) def update_visible(fill_color_mode,image): if image != None: return gr.Row(visible=False),gr.Row(visible=False) if fill_color_mode: return gr.Row(visible=False),gr.Row(visible=True) else: return gr.Row(visible=True),gr.Row(visible=False) with gr.Blocks(css=css, elem_id="demo-container") as demo: with gr.Column(): gr.HTML(read_file("demo_header.html")) gr.HTML(read_file("demo_tools.html")) with gr.Row(): with gr.Column(): image = gr.Image(sources=['upload','clipboard'],image_mode='RGB',elem_id="image_upload", type="pil", label="Upload") box_type = gr.Dropdown(label="box-type",value="type-3",choices=["type-1","type-2","type-3"]) with gr.Row(elem_id="prompt-container", equal_height=False): with gr.Row(): btn1 = gr.Button("Face Crop", elem_id="run_button",variant="primary") btn2 = gr.Button("Face Replace", elem_id="run_button2",variant="primary",visible=False) replace_image = gr.Image(sources=['upload','clipboard'],image_mode='RGB',elem_id="replace_upload", type="pil", label="replace image") replace_image_need_crop = gr.Checkbox(label="Replace image need crop",value=False) with gr.Accordion(label="Advanced Settings", open=False): with gr.Row(equal_height=True): fill_color_mode = gr.Checkbox(label="Fill Color Mode/No Resize",value=False) match_color = gr.Checkbox(label="Match Color",value=True,info="skimage match_histograms") margin_percent = gr.Slider( label="Margin percent",info = "add extra space", minimum=0, maximum=200, step=1, value=0, interactive=True) row1 = gr.Row(equal_height=True) row2 = gr.Row(equal_height=True,visible=False) fill_color_mode.change(update_visible,[fill_color_mode,replace_image],[row1,row2]) with row1: image_size = gr.Slider( label="Image Size",info = "cropped face size", minimum=8, maximum=2048, step=1, value=1024, interactive=True) #filter_image = gr.Checkbox(label="Filter image") filter_value = gr.Dropdown(label="Filter",value="None",choices=["Blur","Smooth More","Smooth","None","Sharpen","Edge Enhance","Edge Enhance More"]) with row2: fill_color = gr.Dropdown(label="fill color",choices=["black","white","gray","red","brown","pink","custom"],value="gray") custom_color = gr.ColorPicker(label="custom color",value="rgba(250, 218, 205, 1)") replace_image.change(update_button_label,replace_image,[btn1,btn2,row1,row2])#margin_percent with gr.Column(): image_out = gr.Image(label="Output", elem_id="output-img") gr.on( [btn1.click,btn2.click], fn=process_images, inputs=[image,replace_image,replace_image_need_crop,box_type,fill_color_mode,fill_color,custom_color,image_size,margin_percent,filter_value,match_color], outputs =[image_out], api_name='infer' ) gr.Examples( examples =["examples/00004200.jpg","examples/00003245_00.jpg","examples/00005259.jpg","examples/00018022.jpg","examples/img-above.jpg","examples/img-below.jpg","examples/img-side.jpg"], inputs=[image] ) gr.HTML(read_file("demo_footer.html")) if __name__ == "__main__": demo.launch()